Is Reverse trial and PLG the strategy to balance CAC and LTV?

Read time: 4 minutes.

Welcome to the 44th edition of The Growth Elements Newsletter. Every Monday, I write an essay on growth metrics & experiments and business case studies.

Today’s piece is for 5,100+ founders, operators, and leaders from businesses such as Shopify, Google, Sage, Hubspot, Servcorp, Zoho, Apollo and more.

Happy Monday!

Is Reverse trial and PLG the strategy to balance CAC and LTV?

Firstly, the reverse trial strategy combines free trials (7, 14, 30 days) and freemium models.

𝐇𝐨𝐰 𝐢𝐭 𝐖𝐨𝐫𝐤𝐬 𝐚𝐧𝐝 𝐁𝐞𝐧𝐞𝐟𝐢𝐭𝐬

[1] 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐜 𝐒𝐲𝐧𝐭𝐡𝐞𝐬𝐢𝐬

► Reverse Trials synthesise the conversion of trials into paying customers with the deep engagement of freemium models.

[2] 𝐕𝐚𝐥𝐮𝐞 𝐋𝐞𝐝 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐢𝐨𝐧

► New users start with a trial, accessing all or a curated selection of premium features, setting the stage for a value-led conversion.

[3] 𝐅𝐥𝐮𝐢𝐝 𝐏𝐫𝐨𝐠𝐫𝐞𝐬𝐬𝐢𝐨𝐧

► Upon trial completion, non-paying users gracefully shift to a freemium plan, ensuring continued access and engagement.

[4] 𝐃𝐮𝐚𝐥 𝐁𝐞𝐧𝐞𝐟𝐢𝐭𝐬

► This strategy marries the proximity of trial deadlines with the open-ended exploration of freemium offerings.

[5] 𝐀𝐜𝐪𝐮𝐢𝐬𝐢𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐑𝐞𝐭𝐞𝐧𝐭𝐢𝐨𝐧

► Reverse Trials are balanced to elevate user acquisition and retention by offering a taste of premium followed by ongoing utility.

[6] 𝐂𝐨𝐧𝐭𝐢𝐧𝐮𝐨𝐮𝐬 𝐄𝐧𝐠𝐚𝐠𝐞𝐦𝐞𝐧𝐭

► The transition to a freemium plan post-trial nurtures long-term user involvement, essential for product loyalty.

[7] 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐢𝐨𝐧 𝐈𝐧𝐜𝐞𝐧𝐭𝐢𝐯𝐞

► Exposure to premium features during the trial can motivate users towards subscription conversion.

[8] 𝐆𝐫𝐨𝐰𝐭𝐡 𝐋𝐨𝐨𝐩 𝐌𝐨𝐦𝐞𝐧𝐭𝐮𝐦

► The sustained engagement from the freemium phase can amplify growth loops, enhancing the product’s adoption.

[9] 𝐁𝐚𝐥𝐚𝐧𝐜𝐞𝐝 𝐌𝐨𝐝𝐞𝐥

► Reverse Trials strive to balance the urgency to convert during the trial period and the long-term engagement offered by freemium plans.

𝐅𝐢𝐧𝐚𝐥 𝐖𝐨𝐫𝐝𝐬

► This approach helps optimise user experience and maximise net growth by balancing CAC and LTV.

► Collectively, both segments of users produce 1000s of data signals, and in conjunction with 10s of growth experiments, it will help increase product adoption.

That's it for today's article! I hope you found this essay insightful.

Wishing you a productive week ahead!

I always appreciate you reading.

Thanks,
Chintan Maisuria